Puchen Zhu

h-index8
2papers
235citations

2 Papers

2.0CVApr 30, 2024
A Minimal Set of Parameters Based Depth-Dependent Distortion Model and Its Calibration Method for Stereo Vision Systems

Xin Ma, Puchen Zhu, Xiao Li et al.

Depth position highly affects lens distortion, especially in close-range photography, which limits the measurement accuracy of existing stereo vision systems. Moreover, traditional depth-dependent distortion models and their calibration methods have remained complicated. In this work, we propose a minimal set of parameters based depth-dependent distortion model (MDM), which considers the radial and decentering distortions of the lens to improve the accuracy of stereo vision systems and simplify their calibration process. In addition, we present an easy and flexible calibration method for the MDM of stereo vision systems with a commonly used planar pattern, which requires cameras to observe the planar pattern in different orientations. The proposed technique is easy to use and flexible compared with classical calibration techniques for depth-dependent distortion models in which the lens must be perpendicular to the planar pattern. The experimental validation of the MDM and its calibration method showed that the MDM improved the calibration accuracy by 56.55% and 74.15% compared with the Li's distortion model and traditional Brown's distortion model. Besides, an iteration-based reconstruction method is proposed to iteratively estimate the depth information in the MDM during three-dimensional reconstruction. The results showed that the accuracy of the iteration-based reconstruction method was improved by 9.08% compared with that of the non-iteration reconstruction method.

3.0ROOct 27, 2021
Dual-Mode Synchronization Predictive Control of Robotic Manipulator

Zhu Dachang, Cui Aodong, Du Baolin et al.

To reduce the contour error of the end-effector of a robotic manipulator during trajectory tracking, a dual-mode synchronization predictive control is proposed. Firstly, the dynamic model of n-DoF robotic manipulator is discretized by using the Taylor expansion method, and the mapping relationship between the joint error in the joint space and the contour error in task space is constructed. Secondly, the synchronization error and the tracking error in the joint space are defined, and the coupling error of joints is derived through the coupling coefficient . Thirdly, a dual-mode synchronization predictive control is proposed, and the stability of the proposed control system is guaranteed using constraint set conditions. Finally, numerical simulation and experimental results are shown to prove the effectiveness of the proposed control strategy.